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“Runoff Modeling in Ghataprabha Sub Basin for Climate Change Scenario”

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“Runoff Modeling in Ghataprabha Sub Basin for Climate Change Scenario” “Runoff Modeling in Ghataprabha Sub basin for Climate Change Scenario” By Nagraj S. Patil , Mr. Nataraj, A. N. B. Gowda, Nagendra VISVESVARAYA TECHNOLOGICAL UNIVERSITY DEPARTMENT OF WATER AND LAND MANAGEMENT Centre for P.G. Studies VTU Belagavi Motivation….. Climate change can be sum up to measurable difference in the values of atmospheric variables such as precipitation, temperature, humidity, wind, solar radiation, atmospheric pressure and other meterological variable over a long period of time. Thus, it is important to quantify the impacts of climate change to frame mitigation and adaptation measures. Hydrological modeling of water cycle in areas with extreme events and natural hazards (e.g., flooding, droughts) is imperative for sustainable management of soil and water resources. Understanding water resources availability would help stakeholders and policymakers to plan and develop an area. The distributed hydrological model can also be used for climate change impact on surface runoff and water availability in the basin catchments. The main aim of this study is to predict surface runoff in the Ghataprabha sub basin catchment using hydrological model SWAT. Objectives The main aim of the study is to simulate the runoff over a Ghatapraha sub basin. Following are the specific objectives are to be achieved. • Multi-site calibration and validation of SWAT Model for Ghataprabha sub basin for the monthly discharge. • Downscaling of climate variables (precipitation, temperature, relative humidity, solar radiation and wind speed) for the Ghataptabha sub basin. • To simulate the surface runoff for the Ghataprabha sub basin using downscaled data from 2021- 2100. • Simulate of streamflow at the four discharge gauge (Bagalkot, Gokak falls, Gotur and Daddi) stations. STUDY AREA Ghataprabha Sub Basin • The Ghataprabha river is an important tributary of the Krishna River. • It flows eastward for a distance of 283 kilometers before joining the River Krishna at Almatti. • The river basin is 8,829 square kilometers wide and stretches across Karnataka and Maharashtra states. Study area Subbasin Ghataprabha(K3) Area 8829 km2 DEM LULC (2011) Source: Cartosat Ver. 3R1 Source: KSRAC, Govt. of Karnataka Soil Source: FAO Data and Its Sources Sl. No Data Source . 1 Precipitation 0.25 x 0.25 degGridded data India Meteorological Department (IMD) 2 Temperature 1.00 x 1.00 deg Gridded data India Meteorological Department (IMD) 3 Digital Elevation Model Bhuvan: Cartosat Ver. 3R1 (32m resolution) 4 LULC 2011 KSRAC GoK 5Soil FAO 6 Discharge Data for Water Resource Information • K3 Sub basin (Bagalkot, Gokak falls, Gotur, System (WRIS) Daddi) Data Source GCM Historical and Future data World Data Center for Climate (WDCC) NCEP-NCAR Reanalysis data NOAA National Center for Relative Humidity Environmental Prediction Solar Radiation U & V Wind components Multisite Calibration and Validation of SWAT Model The calibration and validation of the model is performed manually. The calibration carried out from 1980-1998 with 3 years warm up period. The model is validated from 1999 to 2005. The calibration of the model performed for the Bagalkot gauge and validated with the remaining gauges in the Ghataprabha sub basin. Parameters and their ranges used during calibration Sl.No Parameter Range 1 CN2 80-90 2 ALPHA-BF 0.85-0.95 3 GW_DELAY 0-500 4 GWQMN 1000-2000 5 CH_K2 2-4 6 CH_N2 0.014-0.2 7 EPCO 0.5-1 8 ESCO 0.7-1 9 GW_REVAP 0-0.2 10 RCHRG_DP 0-1 11 REVAPMN 750-1000 12 SOL_AWC 0-1 13 SOL_K 14 SURLAG 0-4 Comparison of Stream Flows Statistical Performance Results Source: D. N. Moriasi et al. 2007 Calibration Validation Station R2 NSE PBIAS RSR R2 NSE PBIAS RSR Bagalkot 0.65 0.81 10.32 0.104 0.99 0.82 -17.17 0.187 Gokak 0.58 0.78 -14.98 0.15 0.70 0.79 -35.85 0.363 Falls Daddi 0.76 0.83 13.93 0.139 0.83 0.82 27.41 0.277 Gotur 0.67 0.43 74.96 0.75 0.67 0.48 71.21 0.72 METHODOLOGY For Downscaling The Climate Variables Source : Examination of change factor methodologies for climate change impact assessment, Anandhi et al. (2011) METHODOLOGY: CHANGE FACTOR METHOD • This method can be used for future projection of climate variable. • This method involves single change factor method which includes additive and multiplicative change factor method. Single additive change factor method Single multiplicative change factor method (Source: Anandhi et. al., 2011) 4. FUTURE PROJECTION Now the change factor values are added to observed IMD data to obtain future climate data. ie., Precipitation(mm) RESULT DISCUSSION AND 10 12 14 16 18 0 2 4 6 8 Jan-41 Jan-42 Jan-43 Monthly precipitation Jan-44 Jan-45 Jan-46 Jan-47 year year 2041-2060 Jan-48 Jan-49 Jan-50 Jan-51 Jan-52 Jan-53 Jan-54 Jan-55 Jan-56 Jan-57 Jan-58 Jan-59 Jan-60 0110034 49.80 25.42 3.44 2.39 16.55 0 2.23 16.63 0 2081-100 2.15 0 2061-80 0 2041-60 2021-40 projection Precipitation 2.6for scenarios Precipitation(mm) Future 10 15 20 25 30 0 5 Jan-61 Feb-62 For RCP scenarios 2.6 Monthly Monthly precipitation Mar-63 Apr-64 May-65 Jun-66 Mean Mini Jul-67 year year 2061-2080 Aug-68 Sep-69 Oct-70 Nov-71 (mm) Dec-72 Jan-74 Feb-75 Mar-76 Apr-77 (mm) Max May-78 Jun-79 Jul-80 Precipitation(mm) Precipitation (mm) 10 20 30 40 50 60 10 12 14 16 18 0 0 2 4 6 8 Jan-81 Jan-21 Jan-82 Jan-22 Jan-83 Monthly precipitation Jan-23 Monthly precipitation Jan-84 Jan-24 Jan-85 Jan-25 Jan-86 Jan-26 Jan-87 Jan-27 year(2081-2100) Jan-88 Jan-28 year year 2021-2040 Jan-89 Jan-29 Jan-90 Jan-30 Jan-91 Jan-31 Jan-92 Jan-32 Jan-93 Jan-33 Jan-94 Jan-34 Jan-95 Jan-35 Jan-96 Jan-36 Jan-97 Jan-37 Jan-98 Jan-38 Jan-99 Jan-39 Jan-00 Jan-40 0110034 42.85 0.00 3.42 2.77 37.06 0 2.91 11.24 0 2081-100 1.84 0 2061-80 0 2041-60 2021-40 projection Precipitation 4.5for scenarios Future Future For For RCP scenarios 4.5 iiMa Max Mean Mini precipitation(mm) 10 12 0 2 4 6 8 Jan-21 Jan-22 Jan-23 Monthly precipitation Jan-24 Jan-25 Jan-26 Jan-27 year(2021-2040) Jan-28 Jan-29 Jan-30 Jan-31 Jan-32 Jan-33 Jan-34 Jan-35 Jan-36 Jan-37 Jan-38 Jan-39 Jan-40 Precipitation for 6.0 scenarios For RCP 6.0 scenarios Future Mini Mean Max projection 2021-40 0 1.72 8.65 2041-60 0 2.23 16.15 2061-80 0 2.63 27.89 2081-100 0 3.64 51.65 Precipitation for 8.5 scenarios For RCP 8.5 scenarios Future Mini M Max projection mm mm 2021-40 0 2.10 15.38 2041-60 0 2.57 23.05 2061-80 0 3.08 31.64 2081-100 0 4.2 63.50 PLOT FOR 2.6 SCENARIO 2021-2100 (Precipitation) BOXPLOT FOR 4.5 SCENARIO 2021-2100 BOXPLOT FOR 6.0 SCENARIO 2021-2100 BOXPLOT FOR 8.5 SCENARIO 2021-2100 Comparison of Tmax of all four scenarios for time period 2021-2100 Tmax of all four scenarios 36 35 °C °C 34 33 TEMPERATURE TEMPERATURE IN 32 31 2020 2030 2040 2050 2060 2070 2080 2090 2100 Months max2.6 max4.5 max6 max8.5 Linear (max2.6) Linear (max4.5) Linear (max6) Linear (max8.5) The mean temperature of 2.6, 4.5, 6 and 8.5 scenarios are 32.40, 32.80, 32.89, 33.82°C respectively. Comparison of Tmin of all four scenarios of time period 2021-2100 Tmin of all four scenarios 26 25 24 °C °C 23 TEMPERATURE IN IN TEMPERATURE 22 21 20 2020 2030 2040 2050 2060 2070 2080 2090 2100 Months min2.6 min4.5 min6 min8.5 Linear (min2.6) Linear (min4.5) Linear (min6) Linear (min8.5) The mean temperature of 2.6, 4.5, 6 and 7.5 scenarios are 21.70, 22.09, 22.18, 22.99°C respectively. Mean, maximum and minimum temperature values T-max T-min 2021-40 2041-60 2061-80 2081-100 2021-40 2041-60 2061-80 2081-100 Max 39.527 40.017 40.439 40.561 27.4 27.638 27.874 27.948 2.6 Scen Min 24.51 23.786 23.171 22.813 11.22 11.359 11.826 11.885 Mean 32.305 32.280 32.563 32.467 21.527 21.626 21.895 21.777 Max 39.631 40.73 40.824 41.42 27.433 28.154 28.449 28.772 Min 24.829 24.506 23.568 23.689 11.18 11.591 12.125 12.627 4.5 Scen Mean 32.351 32.763 32.921 33.169 21.549 22.042 22.304 22.501 Max 39.453 40.278 41.163 41.845 27.453 27.785 28.745 29.29 6.0 Scen Min 24.602 24.155 23.877 23.863 11.276 11.592 12.548 13.088 Mean 32.394 32.501 33.128 33.544 21.575 21.819 22.485 22.859 Max 39.784 42.069 42.069 43.261 27.62 28.603 29.666 30.586 8.5 Scen Min 24.512 24.964 24.964 24.821 11.439 12.19 13.419 14.667 Mean 32.493 34.000 34.000 34.796 21.732 22.408 23.410 24.404 Runoff Simulation at Bagalkot and Daddi discharge gauge from 2021-40 Runoff at Gokak Falls and Gotur discharge gauge from 2021-40 Conclusion This study encompass modelling of hydrological cycle for the Ghataprabha sub basin (K3) to know the streamflow and water availability for the present scenario and to simulate changes in streamflow in the K3 sub basin over a period of time.
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